AIMC Topic: Colonic Polyps
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Use of Endoscopic Impression, Artificial Intelligence, and Pathologist Interpretation to Resolve Discrepancies Between Endoscopy and Pathology Analyses of Diminutive Colorectal Polyps.
Gastroenterology
Dec 18, 2019
An overview of deep learning algorithms and water exchange in colonoscopy in improving adenoma detection.
Expert review of gastroenterology & hepatology
Nov 30, 2019
: Among the Gastrointestinal (GI) Endoscopy Editorial Board top 10 topics in advances in endoscopy in 2018, water exchange colonoscopy and artificial intelligence were both considered important advances. Artificial intelligence holds the potential to...
Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps.
Medical image analysis
Nov 20, 2019
Colorectal polyps are known to be potential precursors to colorectal cancer, which is one of the leading causes of cancer-related deaths on a global scale. Early detection and prevention of colorectal cancer is primarily enabled through manual screen...
Computer-assisted assessment of colonic polyp histopathology using probe-based confocal laser endomicroscopy.
International journal of colorectal disease
Nov 6, 2019
INTRODUCTION: Probe-based confocal laser endomicroscopy (pCLE) is a promising modality for classifying polyp histology in vivo, but decision making in real-time is hampered by high-magnification targeting and by the learning curve for image interpret...
Humans
Machine Learning
Observer Variation
Tumor Burden
Colonic Polyps
Colonoscopy
Image Interpretation, Computer-Assisted
Aged, 80 and over
Diagnosis, Computer-Assisted
Male
Feasibility Studies
Clinical Competence
Female
Middle Aged
Microscopy, Confocal
Colonic Neoplasms
Reproducibility of Results
Predictive Value of Tests
Aged
Automated polyp segmentation for colonoscopy images: A method based on convolutional neural networks and ensemble learning.
Medical physics
Oct 31, 2019
PURPOSE: To automatically and efficiently segment the lesion area of the colonoscopy polyp image, a polyp segmentation method has been presented.
New artificial intelligence system: first validation study versus experienced endoscopists for colorectal polyp detection.
Gut
Oct 15, 2019
Improving Automatic Polyp Detection Using CNN by Exploiting Temporal Dependency in Colonoscopy Video.
IEEE journal of biomedical and health informatics
Apr 1, 2019
Automatic polyp detection has been shown to be difficult due to various polyp-like structures in the colon and high interclass variations in polyp size, color, shape, and texture. An efficient method should not only have a high correct detection rate...
Quality assurance of computer-aided detection and diagnosis in colonoscopy.
Gastrointestinal endoscopy
Mar 26, 2019
Recent breakthroughs in artificial intelligence (AI), specifically via its emerging sub-field "deep learning," have direct implications for computer-aided detection and diagnosis (CADe and/or CADx) for colonoscopy. AI is expected to have at least 2 m...
Artificial intelligence and colonoscopy: Current status and future perspectives.
Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
Feb 27, 2019
BACKGROUND AND AIM: Application of artificial intelligence in medicine is now attracting substantial attention. In the field of gastrointestinal endoscopy, computer-aided diagnosis (CAD) for colonoscopy is the most investigated area, although it is s...
Development and validation of a deep-learning algorithm for the detection of polyps during colonoscopy.
Nature biomedical engineering
Oct 10, 2018
The detection and removal of precancerous polyps via colonoscopy is the gold standard for the prevention of colon cancer. However, the detection rate of adenomatous polyps can vary significantly among endoscopists. Here, we show that a machine-learni...
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